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This study investigates the impact of contract farming in onion, okra and pomegranate production on profits of smallholder farmers in India. It also investigates the determinants of farmers’ participation in contract farming. The study is based on a survey of 1,131 farmers from Maharashtra, India engaged in the cultivation of these three crops.

This study uses instrumental variable regressions and quasi-experimental methods to decipher the impact of contract farming.

The study reveals that contract farming ensures higher returns for smallholders, enables their access to high-end markets and brings in risk-sharing with protection during price fluctuations. Farm size and farmers’ risk perceptions are significantly associated with their participation in contract farming.

The study is based on cross-sectional data, which presents limitations on considering unobserved farmer-level individual heterogeneity.

The study shows that contracts highlight the functioning of the contractor/integrator on both the input and output sides of the market. By providing better-quality inputs on credit and at discounted prices and by providing training, the integrator helps small farmers meet international food safety and quality standards, a historically difficult challenge for smallholders in India.

The purpose of this study is to unfold the existing information channel in the higher moments of currency futures for different time horizons.

The authors use a quasi-Bayesian local likelihood approach within a time-varying parameter vector autoregression (TVP-VAR) framework and a dynamic connectedness measure to study the volatility, skewness and kurtosis of most traded currency futures.

The authors’ results suggest a time-varying presence of dynamic connectedness within higher moments of currency futures. Most spillovers pertain to shorter time horizons. The authors find that in net terms, CHF, EUR and JPY are the most important contributors to the system, while the authors emphasize that the role of being a transmitter or a receiver varies for pairwise interactions and time windows.

To the best of the authors’ knowledge, this is the first study that looks upon the connectivity vis-á-vis uncertainty, asymmetry and fat tails in currency futures within a dynamic Bayesian paradigm. The authors extend the current literature by proposing new insights into asset distributions.

The authors investigate whether firm-specific vulnerability to climate change influences foreign exchange hedging, using a novel text-based measure of firm-level climate change exposure generated by state-of-the-art machine-learning algorithms.

The authors' empirical analysis includes firm-fixed effects, random-effects regressions, propensity score matching (PSM), entropy balancing, an instrumental-variable analysis and using an exogenous shock as a quasi-natural experiment.

The authors' findings suggest that greater climate change exposure brings about a significant reduction in exchange rate hedging. Companies more exposed to climate change may invest significant resources to address climate change risk, such that they have fewer resources available for currency risk management. Additionally, firms seriously coping with climate change risk may view exchange rate risk as relatively less important in comparison to the risk posed by climate change. Notably, the authors also find that the negative effect of climate change exposure on currency hedging can be specifically attributed to the regulatory aspect of climate change risk rather than the physical dimension, suggesting that companies view the regulatory dimension of climate change as more critical.

Recent studies have demonstrated that climatic fluctuations represent one of the most recent sources of unpredictability, thereby impacting the economy and financial markets (Barnett et al., 2020; Bolton and Kacperczyk, 2020; Engle et al., 2020). The authors' study advances this field of research by revealing that company-specific exposure to climate change serves as a significant determinant of corporate currency hedging, thus expanding the existing knowledge base.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Integrating transaction costs economics and task-technology fit theory, this study distinguishes two categories of social media–enabled interactions, namely task-related interactions and tie-related interactions, and explores the match between these two and firms' use of contracts in achieving safeguarding and coordinating purposes in interfirm governance.

Two studies were conducted to test the hypotheses. In Study 1, this study collaborated with a professional market research firm and collected responses from Chinese manufacturing firms in a survey. In Study 2, this study designed a scenario-based experiment and collected 239 participants from the Credamo platform.

This study categorized social media–enabled interactions into task-related interactions and tie-related interactions and conducted two studies to reveal that the safeguarding purpose of contract specificity is amplified by tie-related interactions, whereas the coordinating purpose of contract specificity is strengthened by task-related interactions.

This study assumes that firms permit and encourage the use of social media. However, some firms might prohibit the use of social media due to risk issues, or their partners may be prohibited from using social media.

Given that social media–enabled interactions have joint effects with contracts in achieving safeguarding and coordinating purposes, a firm's employees should match their goals with an appropriate type of social media–enabled interactions.

This study enriches the interfirm governance literature by uncovering the roles of these two types of interactions in matching contract specificity to achieve safeguarding and coordinating purposes, which provides actionable insights for managers in governing interfirm relationships.

This paper aims to review the literature extensively by analysing recent work and providing a guide for models, data sets and research findings.

This paper reviews the literature extensively by analysing recent work and providing a guide for models, data sets and research findings within the context of capital market imperfections. The authors further break down the literature into closer-in-nature categories for reader’s convenience and comprehension. Finally, the authors address gaps in the existing literature and propose government policies that can tone down the potential effect of credit rationing on employment.

This paper provides a map of the literature so as to help future researchers in the relevant literature and give a short insight of what has been explored so far.

This paper is original and is the result of a thorough review of an extensive literature.

This paper attempts to investigate the impact of the Russia–Ukraine war on the returns and volatility of the United States (US) natural gas futures market.

The study uses secondary data of 996 trading day provided by the US Department of Energy and investing.com websites and applies the event study methodology in addition to the generalized autoregressive conditional heteroscedastic (GARCH) family models.

The findings from the exponential EGARCH (1,1) estimate are the best indication of a significant positive effects of the Ukraine–Russia war on the returns and volatility of the US natural gas futures prices. The cumulative abnormal returns (CARs) of the event study show that the natural gas futures prices reacted negatively but not significantly to the Russian–Ukraine war at the event date window [−1,1] and the [−15, −4] event window. CARs for the longer pre and post-event window display significant positive values and coincides with the standard finance theory for the case of the US natural gas futures over the Russia–Ukraine conflict.

This is the first study to examine the impact of the Russia–Ukraine war on natural gas futures prices in the United States. Thus, it provides indications on the behavior of investors in this market and proposes new empirical evidence that help in investment analyses and decisions.

The purpose of this study is to explore how digital transformation helps enterprises achieve high-quality development, including the mediating mechanism of information transparency, innovation capacity and financial stability, the moderating role of financing constraints and government subsidies, and the heterogeneous effects of property rights, size and growth.

This study conducts two-way fixed-effect model using 780 samples of China's Shanghai-Shenzhen A-share listed companies from 2012 to 2019.

The results show that digital transformation can effectively improve the total factor productivity (TFP) of enterprises through the triple channels of information transparency, innovation capability and financial stability. Meanwhile, financing constraints significantly inhibited the contribution of digital transformation to TFP, while government subsidies significantly increased the contribution of digital transformation to TFP. In addition, state-owned enterprises (SOEs), large enterprises and high-growth enterprises are more able to achieve high-quality development by increasing their digital transformation.

In the process of implementing digital transformation, companies should actively improve information transparency, financial stability and innovation capabilities, and choose differentiated paths based on intrinsic characteristics such as property rights, scale and growth. At the same time, the government should actively improve not only the digital institutional environment but also the financial policy and credit system.

This study enriches the theoretical research framework of digital transformation and high-quality development by identifying the channel mechanisms and boundary conditions through which digital transformation affects high-quality development and expands the consequences of digital transformation and the antecedents of high-quality development.

This study aims to use institutional and upper echelons theories to comprehensively investigate the intricate interplay between TMT legal expertise and firms' adaptive strategies in legal contexts, notably within emerging economies. It explores how upper echelons experiences shape opportunistic compliance strategies, impacting value and risk perceptions. Drawing on upper echelons theory, the research probes how TMT legal expertise molds firms’ involvement in significant lawsuits, accounting for influential roles. It scrutinizes TMT’s impact on legal strategies, positing that managerial discretion emerges from environmental factors, organizational attributes and executive traits. The study underscores TMT’s internal incentives and external factors’ interplay, molding strategic legal engagement.

To validate this framework, statistical analysis is performed on data from 2,584 Chinese-listed firms. The data set spans 2010–2015, with 5,713 material lawsuits. Chosen due to reliable institutional-level incentives data from the China Market Index Database, years 2016–2019 are excluded for methodological disparities. Moreover, 2007–2009 is omitted to mitigate the potential financial crisis impact. This study’s 11,272 observations ensure robust empirical exploration, offering insights into the interplay of TMT legal expertise, institutional factors and firms’ legal strategies.

The study reveals that firms led by executives with legal expertise are more prone to engage in significant lawsuits, indicating strategic use of legal skills. TMT age moderates this, with older teams less likely to engage. TMT tenure’s effect remains unclear due to tenure-risk preference complexity. Institutional factors matter; less legally mature regions reduce managers’ legal risk intention. Results confirm hypotheses and highlight executive human capital’s impact on firms’ legal strategies.

This study acknowledges contributions while highlighting limitations, including the need for detailed distinctions in lawsuit roles and exploration of heterogeneous TMT power dynamics. Further research is proposed for nuanced power dynamics and comprehensive TMT legal background data. The study advances upper echelons theory by introducing TMT legal expertise as a factor influencing strategic lawsuit behavior. It challenges institutional theory by showing the adaptable legal context, beyond fixed constraints. Moderating factors – group risk attitude and external knowledge – deepen understanding of upper echelons’ impact. Enhanced data collection is encouraged to address limitations and refine findings.

This study’s implications extend to managerial practices. Firms should acknowledge the dynamic legal system, using TMT legal expertise for strategic legal challenges. Executives should pragmatically approach regulations. While legal professionals enhance compliance, caution is needed in selecting TMT members with legal expertise due to the risk of misusing it for unnecessary litigation, potentially misaligned with financial performance goals.

This study combines institutional and upper echelons theories to explore TMT legal expertise’s impact on firms’ adaptive strategies in emerging economies. It challenges the idea of a universally constraining legal environment and highlights how TMT legal expertise enhances firms’ management of complex legal risks. The research introduces TMT legal expertise as an influencing factor in strategic lawsuits, revealing nuanced relationships between legal contexts and strategic decisions. The findings enrich upper echelons theory, challenge conventional institutional views and identify moderating factors that deepen the understanding of upper echelons’ influence in legal landscapes.

The authors examine the effect of greenhouse gas (ghg) assurance on cost of debt, and the effect of board gender diversity on cost of debt, for an international sample of listed companies.

Utilizing firm-level data and a quantile regression approach, this study examines the effects of greenhouse gas assurance and board diversity on cost of debt by employing an international sample of firms during 2015–2021.

The authors find that in firms with a relatively low cost of debt the external assurance of greenhouse gas emissions and gender diversity could significantly contribute to a reduction of cost of debt. Furthermore, other measures of board diversity that are linked with independent directors and skilled directors seem to contribute to an increase of firms' cost of debt in the lower end of distribution. Drawing from the agency theory, the authors showcase the fact that ghg assurance reduces information asymmetry and therefore agency costs such as borrowing costs and signals to the stakeholders a long-term commitment to excellence.

This study is the first that provides insights on the relationship between ghg assurance, board diversity and cost of debt.